Methods and systems for soft-bit demapping

ABSTRACT

Methods and systems for reconfigurable soft-output bit demapping, reconfigurable for different modes of operation (i.e., different transmitter/receiver configurations) and for different modulation schemes are provided. In an embodiment, a reconfigurable soft-output bit demapping system includes a mode/modulation independent equalizer, a plurality of mode/modulation independent soft-slicers coupled to the outputs of the equalizer, a plurality of mode/modulation independent post-scalers coupled to the outputs of the soft-slicers, and a mode-dependent coefficient calculator. The coefficient calculator generates parameters for configuring the equalizer, the soft-slicers, and the post-scalers according to the used mode of operation and modulation scheme.

CROSS-REFERENCE TO RELATED APPLICATIONS

The present application is a Continuation of U.S. Non-Provisional patentapplication Ser. No. 11/500,405, filed on Aug. 8, 2006, now allowed,which claims the benefit of U.S. Provisional Patent Application No.60/707,524 filed on Aug. 12, 2005, both of which are incorporated hereinby reference in their entireties.

BACKGROUND OF THE INVENTION

1. Field of the Invention

The invention relates to soft-output bit demapping of data symbols.

2. Related Art

Soft-output bit demapping is a process of converting received datasymbols to soft bit values in a coordinate system. The soft bit valuesrepresent a probability that a given data symbol resides at a particularpoint in the coordinate system. A subsequent decoding process willconvert soft bits to hard bits, based in part upon a decryption scheme.

Transmission and reception systems operate in one of a variety of modesof operation. For example, data can be transmitted and received with asingle transmit antenna and a single receive antenna, a single transmitantenna and multiple receive antennas, or with multiple transmitantennas and multiple receive antennas. Conventional demapping systemsare designed for a single mode of operation.

Data can be transmitted using a variety of modulation schemes, such asbinary phase shift keying (“BPSK”), quadrature phase shift keying(“QPSK”), and quadrature amplitude modulation (“QAM”), including 16 bitQAM, 64 bit QAM, and 256 bit QAM. Conventional demapping systems utilizeseparate detectors for each modulation scheme.

Soft-bit demapping for single input/single output systems is taught inTosato and Bisaglia, “Simplified Soft-Output Demapper for BinaryInterleaved COFDM with Application to HIPERLAN/2,” ICC 2002—IEEEInternational Conference on Communications, vol. 25, no. 1, April 2002,pp. 664-668, incorporated herein by reference in its entirety. Soft bitdemapping has not been applied to systems having multiple transmitantennas and multiple receive antennas.

What are needed therefore are methods and systems for soft-bit demappingthat are reconfigurable for different modes of operation and fordifferent modulation schemes.

SUMMARY OF THE INVENTION

The present invention is directed to methods and systems forreconfigurable soft-bit demapping. The methods and systems for soft-bitdemapping are reconfigurable for different modes of operation (i.e.,different transmitter/receiver configurations), and for differentmodulation schemes.

In an embodiment, a reconfigurable soft-bit demapping system includes ageneric, or mode independent, multiple input, multiple output equalizer,a plurality of a generic, or mode independent,single-input/single-output (“SISO”) slicers coupled to the outputs ofthe equalizer, and a mode-dependent coefficient calculator. Thecoefficient calculator generates coefficients for the equalizer and forthe slicers. The equalizer is dynamically reconfigurable to handlemultiple modes of operation. The reconfigurable soft-bit demappingsystem further includes relatively compact logic that allows the slicersto handle a combination of modulation schemes, such as, withoutlimitation, BPSK, QPSK, 16-QAM, 64-QAM, and 256-QAM.

Additional features and advantages of the invention are set forth in thedescription that follows. Yet further features and advantages will beapparent to a person skilled in the art based on the description setforth herein or may be learned by practice of the invention. Theadvantages of the invention will be realized, and attained by thestructure particularly pointed out in the written description and claimshereof as well as the appended drawings.

It is to be understood that both the foregoing summary and the followingdetailed description are exemplary and explanatory and are intended toprovide further explanation of the invention as claimed.

BRIEF DESCRIPTION OF THE DRAWINGS/FIGURES

The present invention will be described with reference to theaccompanying drawings, wherein like reference numbers indicate identicalor functionally similar elements. Also, the leftmost digit(s) of thereference numbers identify the drawings in which the associated elementsare first introduced.

FIG. 1 illustrates various configurations of wireless communicationsystems.

FIG. 2 illustrates an exemplary single-input single-output (SISO)transmit-receive communication chain.

FIG. 3 illustrates an exemplary single-input multiple-output (SIMO)transmit-receive communication chain.

FIG. 4 illustrates an exemplary multiple-input multiple-output (MIMO)transmit-receive communication chain.

FIG. 5 illustrates a SISO soft-output demapper.

FIG. 6 illustrates exemplary equations for generating preliminaryL-values according to various modulation schemes.

FIG. 7 illustrates a reconfigurable multi-mode soft-output demapperaccording to an embodiment of the present invention.

FIG. 8 illustrates equations implemented by a configurable soft-sliceraccording to an embodiment of the present invention.

FIG. 9 illustrates a configurable soft-slicer according to an embodimentof the present invention.

FIG. 10 illustrates another configurable soft-slicer according to anembodiment of the present invention.

FIG. 11 illustrates exemplary control signals for the configurablesoft-slicer embodiment of FIG. 10.

FIG. 12 illustrates another configurable soft-slicer according to anembodiment of the present invention.

FIG. 13 illustrates exemplary control signals for the configurablesoft-slicer embodiment of FIG. 12.

FIG. 14 illustrates a post-scaler according to an embodiment of thepresent invention.

FIG. 15 illustrates another post-scaler according to an embodiment ofthe present invention.

FIG. 16 illustrates an equalizer according to an embodiment of thepresent invention.

FIG. 17 illustrates a coefficient calculator according to an embodimentof the present invention.

FIG. 18 illustrates an exemplary SISO parameterization configuration.

FIG. 19 illustrates exemplary SIMO parameterization configurations.

FIG. 20 illustrates an exemplary MIMO parameterization configuration.

FIG. 21 illustrates an exemplary MIMO coefficient calculatorimplementation.

The present invention will be described with reference to theaccompanying drawings. The drawing in which an element first appears istypically indicated by the leftmost digit(s) in the correspondingreference number.

DETAILED DESCRIPTION OF THE INVENTION Table of Contents I. IntroductionII. Introduction to Soft-Output Demapping III. Re-configurableSoft-Output Demapping

A. Soft-Slicer

B. Post-Scaler

C. Equalizer

D. Coefficient Calculator

IV. Conclusion I. Introduction

Wireless communication systems distinguish between variousconfigurations according to the number of transmit/receive antennas.FIG. 1 illustrates various configurations of wireless communicationsystems.

A single-input single-output (SISO) communication system (illustrated atthe top of FIG. 1) is one characterized by a single transmit antenna 108and a single receive antenna 112, with the wireless communicationchannel serving as a medium for transmitting signals from thetransmitter to the receiver. The wireless communication channel betweentransmit antenna 10S and receive antenna 112 is characterized by achannel response 110 (denoted by in FIG. 1). The channel response h 110indicates the amounts of expected gain and phase changes encountered bya signal s 106 transmitted from transmit antenna 108 to receive antenna112. In other words, the channel response h 110 is a description ofchannel conditions of the wireless communication channel betweentransmit antenna 108 and receive antenna 112. Accordingly, channelresponse h 110 is time-variant and is typically only considered constantover a coherence time of the channel.

Generally, the transmitted signal s 106 is the result of the channelencoding of a message m 102 to generate an encoded message b 104followed by the modulation of b 104 to generate modulated signal s 106.Message m 102 is typically an unprotected binary information sequence.The channel encoding of message m 102 typically includes the insertingof additional bits for error protection. This may be performed accordingto a variety of error coding schemes including, for example,convolutional encoding, cyclic redundancy check (CRC) encoding, or turboencoding. Subsequently, the error-protected message b 104 is modulatedto generate signal s 106, which can be transmitted over the wirelesschannel. Typically, the modulation of message b 104 includes the mappingof information bits of message b 104 into coordinates of a complexconstellation according to the particular modulation scheme being used.This will be further described in section II.

The modulated signal s 106 is typically a complex analog signal.Typically, signal s 106 is frequency up-converted to RF (radiofrequency) before transmission over the wireless channel. For ease ofillustration, this aspect of the communication chain is not shown inFIG. 1

Assuming relatively narrowband transmission, the received signal r 114at receive antenna 112 can be described mathematically according to thefollowing equation:

r=h*s+n  (1)

where n denotes noise added to a channel processed signal (h*s). Thechannel processed signal (h*s) is the result of the multiplication oftransmitted signal s 106 by the channel response h 110 between transmitantenna 108 and receive antenna 112. This multiplication typicallyresults in a scaling and rotation operation of the complex signalrepresentation of signal s.

At the receiver side, the received signal r 114 is first demodulated togenerate a binary information sequence b′. Ideally, b′ 116 is identicalto b 104. b′ 116 is then decoded to generate a message m′ 118. m′ 118 isidentical to m 102 unless errors occurred during transmission.Typically, the decoding of b′ 116 is aided by the error-protectionscheme performed in encoding message m 102.

A single-input multiple-output (SIMO) communication system is alsoillustrated in FIG. 1. The SIMO system includes a single transmitantenna 108 as described above with respect to the SISO system. The SIMOsystem further includes a plurality of receive antennas 124 and 126 atthe receiver side. Note that for ease of illustration, only two receiveantennas 124 and 126 are illustrated in FIG. 1. In general, as can beunderstood by persons skilled in the art, any integer number of receiveantennas can be used.

Similar to the SISO system above, a modulated signal s 108 istransmitted over the wireless channel by transmit antenna 108. Thetransmitted signal s 106 is received respectively at the plurality ofreceive antennas 124 and 126, with received signals r₁ 128 and r₂ 130being respectively related to the transmitted signal s 106 according to:

r ₁ =h ₁ *s+n ₁

r ₂ =h ₂ *s+n ₂  (2)

where (h₁, n₁) and (h₂, n₂) denote respectively the channel response andnoise between transmit antenna 108 and receive antennas 124 and 126.

At the receiver side, received signals r₁ 128 and r₂ 130 contain thesame (single) message m 102 after encoding and modulation to generatethe signal s, the application of channel responses h₁ and h₂, and theaddition of noise, respectively. Received signals r₁ and r₂ are jointlyused to generate a binary sequence b′ 132, which is further decoded togenerate sequence m′ 134. Note that since signals r₁ 128 and r₂ 130contain the same message m 102, the decoding of message m 102 istypically more robust in the SIMO case than in a SISO system. Forexample, if one path between transmit antenna 108 and a receive antennasuffers from high levels of multipath fading, other paths are likely tohave acceptable channel conditions, thereby enhancing the likelihood ofsuccessful communication between the transmit and receive sides.

In similar fashion, SIMO systems can be used to perform beamforming bycombining antenna signals to point in a specific direction. Further,receive combining diversity, where antenna signals are combined tooptimally adapt to local channel conditions, can be achieved using SIMOsystems. One well-known technique is Maximum-Ratio-Combining (MRC), inwhich antenna signals are weighted, phase-aligned, and added in such away as to maximize the signal-to-noise (SNR) ratio.

FIG. 1 further illustrates a multiple-input multiple-output (MIMO)communication system, which includes a plurality of transmit antennas144 and 146 and a plurality of receive antennas 156 and 158. For ease ofillustration, only two transmit antennas 144 and 146 and two receiveantennas 156 and 158 are shown in FIG. 1. However, as would beappreciated by a person skilled in the art, any integer number oftransmit/receive antennas can be used in a MIMO system.

At the transmit side of the MIMO system, a message m 102 is encoded forerror-protection and then divided into a plurality of binary sequencesb₁ 136 and b₂ 138. The plurality of binary sequences b₁ 136 and b₂ 138are then modulated to generate a plurality of signals s₁ 140 and s₂ 142.Signals s₁ 140 and s₂ 142 are then simultaneously transmitted over thewireless channel.

At the receive side of the MIMO system, superpositions of signals s₁ 140and s₂ 142 are received at each of receive antennas 156 and 158. Thereceived signals r₁ 160 and r₂ 162 at receive antennas 156 and 158 arerelated to transmitted signals s₁ 140 and s₂ 142 according to thefollowing:

r ₁ =h ₁₁ *s ₁ +h ₁₂ *s ₂ +n ₁

r ₂ =h ₂₁ *s ₁ +h ₂₂ *s ₂ +n ₂  (3)

where h_(ij) in equations (3) denotes the channel response between thei^(th) receive antenna and the j^(th) transmit antenna in the MIMOsystem, and n1 and n2 denote noise at receive antennas 156 and 158,respectively.

Typically, depending on the channel responses between the varioustransmit and receive antennas, the actual forms in which s₁ and s₂ aresuperimposed at the receive antennas will differ. Accordingly, it is thetask of the receiver to separate out and reconstruct the original binarysequences b₁ 136 and b₂ 138 by exploiting both r₁ and r₂. As shown inFIG. 1, binary sequences b′₁ 164 and b′₂ 166 are generated from receivedsignals r₁ 160 and r₂ 162 and are then decoded and combined to generatea message m′ 168. Given a successful transmission, message m′ 168 isidentical to message m 102. It is noted that in certain environments,such as rich scattering propagation environments, MIMO communication canbe used to increase the throughput of the system.

The present invention is concerned with a multiple-antenna receiverstructure that is capable of operation in all of the above describedcommunication system configurations (SISO, SIMO, and MIMO). In such amultiple-antenna/multiple mode receiver, a SISO scenario may arise fromthe turning off of one or more receive antennas to maintain a singleactive antenna. This may be the case, for example, in a low-powerconfiguration in which one or more receive antennas are switched off toreduce power consumption. Similarly, a SIMO or MIMO scenario arises whenmultiple receive antenna branches are exploited to reconstruct a singleor multiple transmitted signals.

II. Introduction to Soft-Bit Demapping

FIG. 2 illustrates an exemplary single-input single-output (SISO)transmit-receive communication chain. A binary message m 102 is encodedfor error-protection using an encoder 202 to generate an encoded binarysequence b 104. Encoder 202 may be, for example, a convolutionalencoder. Bit-interleaving may also be performed by encoder 202. Bits ofencoded sequence b 104 are modulated using a modulator 204 to generatemodulated signal 106. Signal 106 can be transmitted over the wirelesschannel using transmit antenna 108.

An example modulation of the encoded sequence b 104 is shown in FIG. 2according to a 16-QAM (Quadrature Amplitude Modulation) modulationscheme. According to this scheme, bits (four bits a time) of sequence b104 are mapped to one of 16 constellation points of a complex signalspace 210. For example, bit sequence 1100 of encoded sequence b 104 ismapped to constellation point 212 in complex signal space 210. Themodulated signal s 106 that results from the QAM-modulation of bitsequence 1100 of encoded sequence b 104 is a complex envelope signalhaving real and imaginary parts according to the real and imaginaryparts of constellation point 212 in complex signal space 210.

Modulated signal s 106 is transmitted over the wireless channel (afterfrequency up-conversion) and is received by receive antenna 112.Received signal 114 is mathematically related to transmitted signal s106 as described above in (1). The wireless transmission of signal s 106results in a scaling and rotation operation to the originalconstellation point of signal s 106 in complex signal space 210.Received noise at the receiver further results in a translationoperation to the scaled and rotated constellation point. This isillustrated in received complex signal space 214, where point hs 216corresponds to the scaled and rotated constellation point due towireless transmission and point x 218 corresponds to the receivedconstellation point due to the further addition of noise at thereceiver. Typically, in case of additive Gaussian noise, the point x 218can fall anywhere around the point hs 216.

Various approaches exist to recover the encoded sequence b 104 fromreceived signal r 114. One approach, known as “hard-output demapping”,works by mapping the received point x 218 to the nearest constellationpoint in received complex signal space 214. For example, referring toFIG. 2, point x 218 is mapped to constellation point 220 in complexsignal space 214. Accordingly, bit sequence 1100 would be wronglydemodulated as bit sequence 1101, resulting in low demappingperformance. Another approach, known as “soft-output demapping”, worksby assigning soft-bits or preliminary likelihood values to the bitsencoded in received signal r 114. In FIG. 2, this is performed usingsoft-output demapper (inner receiver) 206. Soft-bits or preliminarylikelihood values indicate how likely is the demapper to consider acertain bit (each of the four) to have value 1 or value 0. One exampleof soft-bits are log-likelihood ratios (LLRs, or L-values), which takepositive values for the bit likely being a logical 1 and negative valuesfor the bit likely being a logical 0, with the larger the absolute valueof the L-value indicating the higher the confidence of the demapper inthe preliminary value. For example, a numeric range of −128 to +127 maybe used, with the value 0 indicating no decision, negative valuesindicating logical 0, positive values indicating logical 1, and valuesclose to the range limits referring to high confidence on the assignedbit polarity.

Accordingly, soft-output demapper 206 generates soft-bits b′ 222 basedon received signal r 114. Soft-bits b′ 222 are used by decoder (outerreceiver) 208 to make hard-decisions on each bit of message m 102,thereby generating message m′ 224. Note that due to redundancy inencoded sequence b 104, more than one bit of soft-bits b′ 222 are usedto make a hard-decision on a single bit of message m′ 224.

FIG. 3 illustrates soft-output demapping in an exemplary single-inputmultiple-output (SIMO) transmit-receive communication chain.

A signal s 106, modulated according to a QPSK (Quadrature Phase ShiftKeying) modulation scheme, is transmitted over a wireless channel and isreceived by receive antennas 124 and 126, respectively. Note thatmodulated signal s 106 is generated by mapping two bits a time ofencoded sequence b 104 to one constellation point in complex signalspace 302. In the example of FIG. 3, the bit sequence 01 is mapped toconstellation point 304.

The transmitted signal s 106 is received at received antennas 124 and126 as received signals r₁ 128 and r₂ 130, respectively. Note that theexample of FIG. 3 illustrates only two receive antennas, but any integernumber of antennas may be used in a general SIMO case. r₁ 128 and r₂ 130are related to s 106 as described in (2) above. The effect of wirelesstransmission and noise on transmitted signal s 106 when received atreceive antennas 124 and 126 is illustrated in FIG. 3 using a complexspace representation. Note that in complex signal representation,signals r₁ 128 and r₂ 130 are scaled, rotated, and translated relativeto signal s 106.

Similar to the SISO case described above, the function of soft-outputdemapper (inner receiver) 206 is to generate soft-bits (or L-values) foreach bit of encoded sequence b 104. In the SIMO case, however,soft-output demapper 206 exploits both received signals r₁ 128 and r₂130 to perform soft-output demapping. Typically, the better the outcomeof the demapping carried in the inner receiver, the higher theprobability that decoder 208 (outer receiver) will be able to estimatethe original message m 102. Often, exploiting received information atone or more antennas has the potential to significantly improve thequality of soft-bits compared to a SISO case. This may be the case, forexample, if one antenna is in a multipath fade but other antennasexhibit strong receive signal.

FIG. 4 illustrates soft-output demapping in an exemplary multiple-inputmultiple-output (MIMO) transmit-receive communication chain. It is notedthat the exemplary communication chain of FIG. 4 illustrates a 2×2 MIMOcase, but can be extended to a more general n×m MIMO case, for anyinteger numbers n and m, as would be appreciated by a person skilled inthe art.

Referring to FIG. 4, a message m 102 is encoded using an encoder 202 togenerate an encoded sequence, which is divided into a plurality ofbinary sequences b₁ 136 and b₂ 138. The binary sequences b₁ 136 and b₂138 are modulated using modulators 402 and 404 to generate modulatedsignals s₁ 140 and s₂ 142, respectively. In the example of FIG. 4,signals s₁ 140 and s₂ 142 are generated according to a QPSK modulationof binary sequences b₁ 136 and b₂ 138. Modulated signals s₁ 140 and s₂142 are transmitted over the wireless channel using transmit antennas144 and 146.

At the receive side, receive antennas 156 and 158 receive superpositionsof transmitted signals s₁ 140 and s₂ 142. Received signals r₁ 160 and r₂162 are mathematically related to s₁ 140 and s₂ 142 as described in (3)above. Complex signal representations 418 and 420 of received signals r₁160 and r₂ 162 are shown in FIG. 4. Note that according to the used QAMmodulation scheme, each of received signals r₁ 160 and r₂ 162 may fallanywhere around any one of 16 different points in received complex space416. These 16 points result from all possible summations of each (scaledand rotated) constellation point of the s₁ transmit constellation spaceand each (scaled and rotated) constellation point of the s₂ transmitconstellation space.

Similar to the SIMO case, soft-output demapper (inner receiver) 206makes use of the various received signals r₁ 160 and r₂ 162 to generatesoft-bits (or L-values) W₁ 406 and b′₂ 408 for binary sequences b₁ 136and b₂ 138, respectively. The soft-bits are then used by decoder 208 togenerate an estimate message m′ 224 of message m 102.

FIG. 5 illustrates a conventional SISO soft-output demapping scheme 500.A received signal (r=h*s+n) 114 is first multiplied by a signal 502 ofvalue 1/h, where h is the channel response of the wireless channel. Themultiplication of r by 1/h has the effect of removing the scaling androtation due to wireless channel transmission of the transmitted signals. Note that the channel response h is typically estimated using anindependent Channel Estimation procedure. The resulting signal (y=s+n′)504 is the equivalent of the original transmitted signal s, translatedin complex space by a noise signal n′=n/h, where n is the noise atreceive antenna 112.

Subsequently, a soft-slicer on integer grid 506 performs soft-outputdemapping using y 504, to generate soft-bits or preliminary L-values 508for bits contained in received signal r 114. Further, to account for thesignal-to-noise ratio (SNR) in the generated L-values 508, thepreliminary L-values 508 are multiplied by a signal 510 of value |h²| togenerate final L-values 512.

Ideally, a soft-bit demapper implements Maximum Likelihood (ML)demapping, which provides superior detection performance. ML demappingis well known in the art of SISO demapping. Traditionally, ML demappinghas been achieved for single-transmit antenna systems (that is, singletransmit stream systems such as SISO and SIMO), but is difficult toimplement for multiple transmit antenna systems (i.e., MIMO).

In the case that Gray coding is used in the modulation schemeconstellation (i.e., QAM constellations in which adjacent points onlydiffer in one bit position), a scheme by Tosato and Bisaglia exists toreliably generate preliminary L-values based on signal y 504. Thisscheme is taught in Tosato and Bisaglia, “Simplified Soft-OutputDemapper for Binary interleaved COFDM with Application to HIPERLAN/2,”ICC 2002—IEEE International Conference on Communications, vol. 25, no.1, April 2002, pp. 664-668, and has its equations for generatingpreliminary L-values derived in FIG. 6 for some of the main QAMmodulation schemes (BPSK, QPSK, 16-QAM, 64-QAM, and 256-QAM). Thepreliminary L-values are denoted by the Λ variables in FIG. 6. For QPSK,Λ_(R,0) refers to the L-value of the first bit of the transmitted 2-bitsequence and Λ_(I,0) refers to the L-value of the second bit of thetransmitted 2-bit sequence. For 16-QAM, Λ_(R,0), Λ_(I,0), Λ_(I,1) referrespectively to the preliminary L-values of the first, second, third,and fourth bit of the transmitted 4-bit sequence. A similar namingconvention is used for the equations of the 64-QAM and 256-QAM cases.

Nonetheless, the soft-output demapping scheme of FIG. 5 suffers from anumber of limitations including requiring a computationally extensivedivision (division by h), being limited to SISO systems, and providingless than optimal performance when successive received symbols r havedifferent noise power levels.

III. Re-Configurable Soft-Output Demapping

Methods and systems for reconfigurable soft-output bit demapping areprovided below. A soft-output bit demapper described herein isdynamically reconfigurable for multiple modes of operation (i.e.,transmitter/receiver configurations), and multiple modulation schemes.For example, and without limitation, a dynamically reconfigurablesoft-output bit demapper can be reconfigured for a single transmitantenna and a single receive antenna (i.e., single input/single output,or SISO), a single transmit antenna and multiple receive antennas (i.e.,single input/multiple output, or SIMO), and with multiple transmitantennas and multiple receive antennas (i.e., multiple input/multipleoutput, or MIMO). A soft-output bit demapper described herein is alsodynamically reconfigurable for multiple modulation schemes including,without limitation, BPSK, QPSK, and QAM.

A demapper system as described herein provides high detection quality(i.e., high quality of soft-bits), and can be implemented in arelatively compact, relatively inexpensive configuration with lowcomplexity

In an embodiment, a reconfigurable soft-output demapper includes genericor mode/modulation independent (mode/modulation-agnostic) equalizer,soft-slicer, and post-scaler and a mode/modulation dependent coefficientcalculator for configuring the mode/modulation-agnostic equalizer,soft-slicer, and post-scaler. In an embodiment, the reconfigurablesoft-output demapper uses a set of configuration parameters(coefficients) for the equalizer, soft-slicer, and post-scaler,consistent between modes, to achieve relatively low dynamic range acrossall modes while maintaining a relatively high quality of finalsoft-bits.

FIG. 7 illustrates an example reconfigurable multi-mode soft-outputdemapper 700 including a mode/modulation-agnostic equalizer 702, aplurality of mode/modulation-agnostic soft-slicers 730 and 732, aplurality of mode/modulation-agnostic post-scalers 738 and 740, and acoefficient calculator 712. Note that FIG. 7 illustrates thereconfigurable multi-mode soft-output demapper for the n×2 MIMO case,which can be readily extended to the n×m MIMO case for any integer m.

Equalizer 702 pre-processes one or more received signal streams r₁ 704and r₂ 706 according to a weight matrix W 746, provided by coefficientcalculator 712. The weight matrix W 746 is typically generated bycoefficient calculator 712 using a channel response matrix H 714 andnoise variances 716 associated with the one or more received streams.Weight matrix W 746 may depend on the mode of operation of demapper 700.In an embodiment, equalizer 702 corrects received streams r₁ 704 and r₂706 for channel effects and noise interference. At the output, equalizer702 generates one or more equalized signals y₁ 708 and y₂ 710. Note thatequalizer 702 eliminates the need for the computationally extensivedivision by h, described above with respect to FIG. 5.

Equalized signals y₁ 708 and y₂ 710 are received by respectivesoft-slicers 730 and 732, which generate soft-bits from equalizedsignals y₁ 708 and y₂ 710. In an embodiment, soft-slicers 730 and 732utilize Maximum Likelihood demapping to generate the sot-bits.Soft-slicers 730 and 732 are configurable by coefficient calculator 712,which provides soft-slicers 730 and 732 with REF_1 signal 726 and REF_2signal 728, respectively. REF_1 726 and REF_2 728 include mode-related(SISO, SIMO, or MIMO) parameters for configuring soft-slicers 730 and732. Soft-slicers 730 and 732 also receive QAM_1 signal 722 and QAM_2signal 724 from a receiver control module 718. QAM_1 722 and QAM_2 724include modulation-related (e.g., BPSK, QPSK, QAM) parameters forconfiguring soft-slicers 730 and 732. Note that signals QAM_1 722 andQAM_2 724 are independent, thereby allowing for soft-slicers 730 and 732to simultaneously operate according to different modulation schemes(different modulation scheme per branch).

Post-scalers 738 and 740 receive the soft-bits generated by soft-slicers730 and 732, respectively, and scale the soft-bits using scaling factorsto generate final soft-bits 742 and 744. The scaling factors used bypost-scalers 738 and 740 are both mode and modulation dependent. In anembodiment, post-scalers 738 and 740 receive SCALE_1 734 and SCALE_2 736signals from coefficient calculator 712. In an embodiment, SCALE_1 734and SCALE_2 736 are generated by coefficient calculator 712 using noisevariance signals 716. Post-scalers 738 and 744 also receive QAM_1 722and QAM_2 724 signals from receiver control module 718. Accordingly,post-scalers 738 and 740 scale the soft-bits generated by soft-slicers730 and 732 to ensure that the final soft-bits 742 and 744 have similardynamic ranges both for the various modes of operation and for thevarious signal-to-noise conditions (across both all receive branches andsuccessive received symbols per branch).

Various embodiments of components of the re-configurable soft-outputdemapper (soft-slicers, post-scalers, equalizer, and coefficientcalculator) are provided below.

A. Soft-Slicers

As described above, the re-configurable soft-output demapper includesone or more mode/modulation-agnostic soft-slicers. In an embodiment, thesoft-slicers are configurable soft-slicers, which implement MaximumLikelihood soft-slicing. In an embodiment, each of the one or moresoft-slicers implements one or more equations for generating soft-bits(or preliminary L-values) based on received equalized signal streams.

FIG. 8 illustrates example equations implemented by a configurablesoft-slicer. The equations of FIG. 8 are provided for various modulationschemes including BPSK, QPSK, 16-QAM, 64-QAM, and 256-QAM. It is notedthe recursive nature of the equations of FIG. 8 for the variousmodulation schemes, where values of certain soft-bits are used in thecomputation of subsequent soft-bits. For example, for 16-QAM, thepreliminary L-value Λ_(R,1) of the second bit is calculated using thepreliminary L-value Λ_(R,0) of the first bit. This significantly reducesthe computational complexity of soft-bits and results in compactsoft-slicer implementations. Also noted in the equations of FIG. 8 isthe use of a mode-dependent constant REF and a modulation-dependentconstant K. These constants are typically received from the coefficientcalculator and the receiver control module. In an embodiment, K is givenaccording to the following:

BSPK: K=1

QPSK: K=1/√2

16-QAM: K=1/√10

64-QAM: K=1/√42

256-QAM: K=1/√170.

FIG. 9 illustrates an exemplary configurable soft-slicer 900.Soft-slicer 900 implements the equations of FIG. 8 for generatingsoft-bits.

Soft-slicer 900 receives an equalized signal y 902. The equalized signaly 902 is divided into its real and imaginary parts y_(R) 904 and y_(I)906, with the real part y_(R) 904 used to generate the Λ_(R) soft-bitvalues and the imaginary part y_(I) 906 used to generate the Λ_(I)soft-bit values. Note that, for ease of illustration, only the portionof soft-slicer 900 that generates Λ_(R) soft-bit values is illustratedin FIG. 9, with the portion for generating Λ_(I) soft-bit values beingsubstantially similar.

Soft-slicer 900 includes a multiplexer 910, which receives a QAM signal908 and outputs a modulation-dependent constant K 912 in accordance withthe used modulation scheme. In an embodiment, multiplexer 910 receivesQAM signal 908 from the receiver control module of the soft-outputdemapper. The modulation-dependent constant K 912 is multiplied by amode-dependent constant REF 914, with the multiplication resultsubsequently used in generating the soft-bit values. REF 914 istypically received from the coefficient calculator in the soft-outputdemapper.

Soft-slicer 900 generates soft-bits for a plurality of modulationschemes as illustrated in FIG. 9. In an embodiment, the soft-bit valuefor the first bit (Λ_(R,0)) is generated directly from the real party_(R) 904 of the received equalized signal y 902. This value issubsequently recursively used to generate soft-bit values for subsequentbits in the received equalized signal y 902. For example, for 16-QAMmodulation, Λ_(R,0) is subtracted from signal 922 having value 2*REF*Kto generate Λ_(R,1).

At the output of soft-slicer 900, an output multiplexer 918 controlledby a readout control module 916 selects output L-values 920 from thegenerated soft-bits, according to the used modulation scheme. In anembodiment, the readout control module 916 is controlled by QAM signal908, which is provided by the receiver control module.

FIG. 10 illustrates a configurable soft-slicer 1000 according to anotherembodiment of the present invention. For ease of illustration, only theportion of soft-slicer 1000 that generates Λ_(R) soft-bit values isillustrated in FIG. 10, with the portion for generating Λ_(I) soft-bitvalues being substantially similar.

Similar to the soft-slicer embodiment of FIG. 9, soft-slicer 1000includes a multiplexer 908 that outputs the modulation-dependentconstant K 912 and an output multiplexer 918 for outputting L-values920.

On the other hand, soft-slicer 1000 employs bit-shift structures 1006,1008, and 1010 to alternatively perform the factor of 2 multiplicationoperations, implemented in the embodiment of FIG. 9. It is known that ann-bit bit-shift is the equivalent of a multiplication by 2^(n). In anembodiment, bit-shift structures 1006, 1008, and 1010 are controlled bya shift control module 1002, which provides the bit-shift structureswith configuration parameters n₁, n₂, and n₃ according to the usedmodulation scheme, In an embodiment, the shift control module 1002receives QAM 908 signal from the receiver control module of thesoft-output demapper.

As a result, the number of operations (summations, absolute valuecalculations) within the soft-slicer is reduced. Further, the embodimentof FIG. 10 allows for the aggregation of computation branches within thesoft-slicer among the various modulation schemes. Note, for example,that in FIG. 9, 16-QAM, 64-QAM, and 256-QAM have each a separatecomputation branch for Λ_(R,1), but that a single Λ_(R,1) computationbranch exists in FIG. 10 for all modulation schemes. As such, outputmultiplexer 918 only needs to ensure that the correct number ofsoft-bits is output (i.e., 1 in BPSK, 2 in QPSK, 4 in 16-QAM, 6 in64-QAM, and 8 in 256-QAM).

FIG. 11 illustrates exemplary control signals for configuringsoft-slicer 1000 of FIG. 10. The control signals aremodulation-dependent and include K constants, bit shift control signals,and read out control signals.

FIG. 12 illustrates a configurable soft-slicer 1200 according to anotherembodiment of the present invention. Soft-slicer 1200 exploits therecursive nature of the soft-output demapping equations of FIG. 8 toimplement a serial computation of preliminary L values for a givenmodulation scheme.

In an embodiment, soft-slicer 1200 employs a feedback loop including anabsolute value calculation module 1216 and a delay structure 1214 tosuccessively compute soft-bits. Soft-slicer 1200 further includes an I/Qselect module 1204 to select the real part 904 or the imaginary part 906of the received equalized signal y 902. The I/Q select module 1204 iscontrolled by an IQ select signal 1202. The feedback loop and the output1206 of the I/Q select module 1204 are input into a multiplexer 1210.Multiplexer 1210 is controlled by a control signal f_sel 1212, whichdetermines which of the two inputs of multiplexer 1210 is output at eachclock cycle.

Similar to above described soft-slicer embodiments 900 and 1000,soft-slicer embodiment 1200 includes a multiplexer 910 that outputs themodulation-dependent constant K 912. The constant K 912 is multiplied bymode-dependent signal REF 114, with the product further multiplied by afactor of 2, according to the modulation scheme. The factor of 2multiplication is implemented using a bit-shift structure 1208, which iscontrolled by a control signal n 1226.

The output of multiplexer 1210 is subtracted from the output ofbit-shift structure 1208 to generate soft-bit values 1228. For certainsoft-bits, a sign inversion operation is optionally performed usinginverter 1220. It is noted that in FIG. 12, a single soft-slicingstructure is provided to process both the real and imaginary parts ofthe received equalized signal y 902. In other embodiments, the structureof FIG. 12 can be duplicated for simultaneous processing of the real andimaginary parts of y 902, resulting in faster generation of soft-bits1228.

In an embodiment, a control module 1222 is used to provide soft-slicer1200, at each clock cycle, with the required control parameters (n, inv,iq_sel, k_sel, and f_sel) based on the used modulation scheme. FIG. 13illustrates an exemplary (time) configuration of control parameters ofsoft-slicer 1200, for various modulation schemes. It is noted that atthe beginning of demapping of the first bit on both the real andimaginary parts of y 902, delay structure 1214 is reset to zero. Inother words, delay structure 1214 is reset to zero before clock cyclec=0 for all modulation schemes. Further, a reset of delay structure 1214is performed just before c=2 in 16-QAM, just before c=3 in 64-QAM, andjust before c=4 in 256-QAM. Also, note that when parameter n is set be“off”, no signal should be injected to the feedback loop. In practice,this can achieved by disabling the output of bit-shift structure 1208(i.e., setting the output to constant 0) and having a separate“enable/disable” signal instead of encoding the request to generate anall-zeros output.

B. Post-Scaler

The re-configurable soft-output demapper optionally includes a pluralityof mode/modulation-agnostic post-scalers. In FIG. 7, the post-scalersare illustrated as soft-output demapper elements 730 and 732.

FIG. 14 illustrates an exemplary post-scaler implementation 1400according to an embodiment of the present invention. As described above,the function of a post-scaler is to scale the soft-bits generated by thesoft-slicer to account for varying signal-to-noise ratio (SNR)conditions at the receiver.

Post-scaler 1400 receives a soft-bit value A 1402 from a soft-slicer.The soft-bit value 1402 is multiplied by mode/modulation dependentfactor 1404 to generate a final L-value 1406.

In an embodiment, the mode/modulation dependent factor 1404 is generatedby multiplying a scaling constant SCALE 1410 provided by the coefficientcalculator (not shown in FIG. 14) and a modulation dependent constant1416. The scaling constant 1410 is related to signal-to-noise ratio(SNR) conditions at the receiver. In an embodiment, the modulationdependent constant 1416 is generated by bit-shifting a factor K outputby a multiplexer 1412 of post-scaler 1400. In an embodiment, multiplexer1412 receives as input a number of modulation dependent constants andoutputs a particular constant according to the used modulation scheme.In an embodiment, multiplexer 1412 is controlled by a QAM 1408 signalprovided by the receiver control module of the soft-output demapper.

In an embodiment, post-scaler 1400 performs the following equation:

L=Λ*SCALE*4*K  (4)

where L is the final L-value and Λ is the received soft-bit value. Notethat the constant scaling by 4 is selected according to numerical rangeconsiderations of the final L-values and that other scaling constantsmay also be used.

FIG. 15 illustrates another post-scaler implementation 1500. Thepost-scaler implementation 1500 is a log domain-equivalent ofimplementation 1400 of FIG. 14. Note that multiplication operations inthe embodiment of FIG. 14 are replaced with addition operations in theembodiment of FIG. 15. This is the case because multiplicationsperformed in a linear domain are functionally equivalent to additionsperformed in a logarithmic domain.

A received soft-bit value 1402 can be transformed into the log domainusing a linear to log transformer 1502, to generate a log soft-bit value1510. Subsequently, the generated log soft-bit value 1510 is summed witha mode/modulation dependent factor 1512, with the summation resulttransformed back to the linear domain (using log to linear transformer1504) to generate the final L-value 1406.

It is noted that in log implementation 1500, the scaling constant 1508provided by the coefficient calculator and inputs into multiplexer 1412are provided in the log domain. Further, note that the bitshiftoperation performed in implementation 1400 using bitshift structure 1414is replaced with an addition operation of a constant.

C. Equalizer

The re-configurable soft-output demapper includes amode/modulation-agnostic equalizer. In FIG. 7, the equalizer isillustrated using soft-output demapper element 702.

As described above, the function of the equalizer is to pre-processreceived streams according to a weight matrix provided by thecoefficient calculator of the demapper. The weight matrix is typicallygenerated using a channel response matrix and noise variances associatedwith the received streams. As a result, the equalized streams arecorrected for any channel effects, such as rotation and scaling, andnoise effects such as translation.

FIG. 16 illustrates an exemplary equalizer 1600. As illustrated, theequalizer 1600 receives a plurality of streams r₁ 1602 and r₂ 1604 and aweight matrix W 1610 and outputs a plurality of corresponding equalizedstreams y₁ 1606 and y₂ 1608. As would be understood by a person skilledin the art, equalizer 1600 illustrates a 2 receive antennas case but canbe readily extend to a more general m receive antennas SIMO or MIMOcase.

FIG. 16 further illustrates the matrix multiplication operationperformed in equalizer 1600, which includes a multiplication of weightmatrix W and a vector of received streams [r₁ r₂] to generate a vectorof equalized streams [y₁ y₂]. Note for a single receive antenna case,the matrix multiplication reduces to scalar multiplication. Also it isnoted that the number of received streams at the equalizer is equal tothe number of receive antennas at the receiver and that the number ofequalized streams generated by the equalizer is equal to the number oftransmitted streams by the transmitter.

D. Coefficient Calculator

The re-configurable soft-output demapper includes a coefficientcalculator to configure elements of the demapper according to themodulation scheme and the mode of operation. In FIG. 7, the coefficientcalculator is illustrated as element 712 of the soft-output demapper.

FIG. 17 illustrates a coefficient calculator 1700 according to anembodiment of the present invention. In an embodiment, coefficientcalculator 1700 receives a channel response matrix estimate H 1702 andnoise variances 1704 for each receive branch of the receiver. Further,coefficient calculator 1700 receives a control signal CTRL 1704 for thereceiver control module of the receiver, which indicates to thecoefficient calculator the mode of operation (SISO, SIMO, MIMO) and theused modulation scheme.

Based on these received inputs, coefficient calculator 1700 calculates anumber of configuration parameters including a plurality ofmode-dependent parameters 1708 (REF_1 and REF_2 in FIG. 17) forconfiguring the soft-slicers, a plurality of scaling factors 1712(SCALE_1 and SCALE_2 in FIG. 17) used by the post-scalers, and a weightmatrix W 1710 used by the equalizer.

The coefficient calculator enables the equalizer to accommodate multipletransmit/receive modes of operation, including, without limitation, asingle transmit antenna and a single receive antenna, a single transmitantenna and multiple receive antennas, and multiple transmit antennasand multiple receive antennas. Similarly, the coefficient calculator 102enables the slicers to accommodate multiple modulation schemesincluding, without limitation, BPSK, QPSK, and QAM.

Note that for a given mode of operation, there is generally a number ofvalid parameterizations for the equalizer, the soft-slicers, and thepost-scalers to generate desired L-values at the output of thesoft-output demapper. It is desirable to employ configurations whichexhibit good numerical properties, allowing for a compact andcost-efficient hardware implementation. One criterion relates to thedynamic range of signals, in that the range of values generated by thesoft-output demapper for any received signals should be representablewithout significant loss of accuracy using a fixed-point representation.Accordingly, the coefficient calculator should ensure a finite dynamicrange of generated values across all modes of operation, modulationschemes, and channel and noise conditions.

In the following, a number of exemplary parameterization configurationsfor different modes of operations are provided. It is noted that theseconfigurations are provided for the purpose of illustration and are notlimiting. Other configurations may also be implemented.

FIG. 18 illustrates an exemplary parameterization configuration for aSISO mode of operation. It is noted that in this mode of operation,signal 1704 that provides noise variance information to the coefficientcalculator includes information of a single receive branch. Further,since this mode of operation includes a single transmit antenna and asingle receive antenna, the weight matrix W 1710 includes a singlenonzero entry.

The coefficient calculator outputs a single mode-dependent REF_1 1708signal and a single scaling factor SCALE_1 1712, with values asillustrated in FIG. 18 according to this particular exemplaryconfiguration. This is the case because with a single received stream, asingle post-slicer and single post-scaler is used.

FIG. 19 illustrates exemplary parameterization configurations for a SIMOmode of operation. In these exemplary configurations, a case with tworeceive antennas is assumed. This, however, can be readily extended to amore general SIMO case with any number of receive antennas, as would beappreciated by a person skilled in the art based on the teachingsherein.

It is noted that since a single transmit stream is present, only weightsW₁₁ and W₁₂ of weight matrix W are relevant in these exemplaryconfigurations. Similarly, since a single post-slicer and a singlepost-scaler are used for a single transmit stream, a singlemode-dependent parameter REF_1 and a single scaling factor SCALE_1 needto be calculated by the coefficient calculator.

FIG. 19 provides a first (Option #1) and a second (Option #2) exemplaryconfiguration, with either providing a valid parameterization of thesoft-output demapper. The choice between either configuration may dependon the complexity of the solution and/or numerical properties of theoverall soft-output demapper. Other hybrid parameterizations may useboth the first and second configurations.

The following exemplary parameterizations may be used using the firstand second exemplary configurations of FIG. 19:

-   -   A) always use Option #1.    -   B) always use Option #2.    -   C) use Option #1 whenever N₂>N₁, otherwise use Option #2.    -   D) use Option #1 whenever N₁>N₂, otherwise use Option #2.    -   E) use Option #1 whenever (N₂/N₁)|H₁₁|²>(N₁/N₂)|H₂₁|², otherwise        use Option #2.    -   F) use Option #1 whenever (N₁/N₂)|H₂₁|²>(N₂/N₁)|H₁₁|², otherwise        use Option #2.

Note that in all of above listed parameterizations, replacing the “>”sign (larger than) by a “>=” sign (larger than or equal) also results inuseful parameterizations that exhibit good performance in practice. Alsonote that in parameterizations C) through F), the choice between Option#1 and Option #2 is perfomed at run-time (e.g., as soon the channelcoefficients H₁₁ and H₂₁ and the noise variances N₁ and N₂ becomeavailable).

FIG. 20 illustrates an exemplary MIMO parameterization configuration. Inthis exemplary configuration, a case with two transmit antennas and tworeceive antennas is assumed. This, however, can be readily extended to amore general MIMO case with any number of transmit/receive antennas, aswould be appreciated by a person skilled in the art based on theteachings herein.

It is noted that various terms of the exemplary configuration of FIG. 20require the computation of the term |H_(det)|=|H₁₁H₂₂−H₂₁H₁₂|. Anefficient implementation of portions of the coefficient calculator usingCORDIC structures is provided below with respect to FIG. 21. It is alsonoted that the computation of scaling factors SCALE_1 and SCALE_2requires division operations, which may be more efficiently implementedin the logarithmic domain. In such implementation, the coefficientcalculator calculates in the logarithmic domain the numerator |H_(det)|of factors SCALE_1 and SCALE_1 as well as the denominator terms of thesefactors as illustrated in FIG. 20. The logarithmic domain values of thefactors SCALE_1 and SCALE_2 can then be computed as follows:

SCALE_(—)1=log(|H _(det)|)−log(N ₁ |H ₂₂|² +N ₂ |H ₁₂|²),

SCALE_(—)2=log(|H _(det)|)−log(N ₁ |H ₂₁|² +N ₂ |H ₁₁|²)

where typically the log operation is performed as a base-2 log.

FIG. 21 illustrates an exemplary MIMO coefficient calculatorimplementation 2100. It is noted that implementation 2100 illustratesthe portions of the MIMO coefficient calculator that compute REF_1,REF_2, the weight matrix W, and the numerator of the scaling factorsSCALE_1 and SCALE_2. The portions of the coefficient calculator thatcompute the denominators of scaling factors SCALE_1 and SCALE_2 are notillustrated in FIG. 21. It is also noted that channel responsecoefficients H₀₀, H₀₁, H₁₀, and H₁₁ in FIG. 21 correspond respectivelyto channel coefficients H₁₁, H₁₂, H₂₁, and H₂₂ in FIG. 20. Similarly,weight coefficients W₀₀, W₀₁, W₁₀, and W₁₁ correspond respectively toweight coefficients W₁₁, W₁₂, W₂₁, and W₂₂ of channel matrix W of FIG.20.

According to implementation 2100, a determinant H_(det) 2108 of channelresponse matrix H is computed using multipliers 2102 and 2104 and asummer 2106 from received channel coefficients H₀₀, H₀₁, H₁₀, and H₁₁.Subsequently, a master CORDIC structure 2110 is used to generate theabsolute value |H_(det)| 2112 of the determinant H_(det) 2108.Typically, the master CORDIC structure 2110 performs iterative rotationsin complex space on the complex-valued H_(det) 2108 until its complexpart is substantially equal to zero, resulting in a real-only valueequal to the absolute value of H_(det) 2108. Concurrently, iterativephase rotations are applied on channel coefficients H₀₀, H₀₁, H₁₀, andH₁₁ using Slave CORDIC structures 2114, 2116, 2118, and 2120 to generateweight coefficients W₀₀, W₀₁, W₁₀, and W₁₁. Note that the overall phaserotation applied to H_(det) 2108 is equal to the overall phase rotationapplied to each of channel coefficients H₀₀, H₀₁, H₁₀, and H₁₁. This ishighlighted by the Master-Slave relationship between CORDIC structure2110 and CORDIC structures 2114, 2116, 2118, and 2120, with MasterCORDIC structure 2110 controlling Slave CORDIC structures 2114, 2116,2118, and 2120 using a control signal 2122.

Above, a number of various parameterization configurations have beenprovided for various modes of operation, While other validconfigurations are possible, the above described configurations arecharacterized by a relatively low dynamic range for all signals. Asillustrated in FIG. 18, for example, the weight coefficient W₁₁ is givenby H₁₁*. Similarly, for the two SIMO options of FIG. 19, W₁₁ is given byeither the same value or a scaled version thereof. Accordingly, W₁₁exhibits a linear dependency on a channel coefficient. The same appliesfor the other weight coefficients of weight matrix W. Note that phaserotation does not change the absolute value of the weights, and hencedoes not affect their dynamic range. Therefore, in all three modes ofoperation, the weight coefficients are linear functions of a channelcoefficient, limiting the numerical range of the equalizer outputs tothe ranges of its input signals multiplied by an expression that islinearly proportional to a channel coefficient.

IV. Conclusion

The present invention has been described above with the aid offunctional building blocks illustrating the performance of specifiedfunctions and relationships thereof. The boundaries of these functionalbuilding blocks have been arbitrarily defined herein for the convenienceof the description. Alternate boundaries can be defined so long as thespecified functions and relationships thereof are appropriatelyperformed. Any such alternate boundaries are thus within the scope andspirit of the claimed invention. One skilled in the art will recognizethat these functional building blocks can be implemented by discretecomponents, application specific integrated circuits, processorsexecuting appropriate software and the like and combinations thereof.

While various embodiments of the present invention have been describedabove, it should be understood that they have been presented by way ofexample only, and not limitation. Thus, the breadth and scope of thepresent invention should not be limited by any of the above-describedexemplary embodiments, but should be defined only in accordance with thefollowing claims and their equivalents.

1. A receiver, comprising: an equalizer that equalizes a received datastream to generate an equalized data stream; a soft-bit slicer, coupledto the equalizer, that receives the equalized data stream and generatesone or more preliminary soft-bit values, said preliminary soft-bitvalues corresponding to one or more bits of a data symbol contained inthe received data stream; and a post-scaler that scales said preliminarysoft-bit values to generate final soft-bit values; wherein the soft-bitslicer is configured to iteratively generate said preliminary soft-bitvalues, whereby a preliminary soft-bit value corresponding to a firstbit of the data symbol is used to generate preliminary soft-bit valuescorresponding to subsequent bits of the data symbol.
 2. The receiver ofclaim 1, further comprising: a coefficient calculator, coupled to theequalizer and the soft-bit slicer, that provides configurationparameters to the equalizer and the soft-bit slicer according to adesired mode of operation and modulation scheme of the receiver.
 3. Thereceiver of claim 2, wherein the coefficient calculator provides theequalizer with a matrix of weight coefficients representative of channelresponse and noise estimates, and wherein the equalizer multiplies saidreceived data stream by said weight matrix to generate said equalizeddata stream.
 4. The receiver of claim 1, wherein the equalizer isconfigurable to accommodate one or more of the followingtransmit/receive antenna modes of operation: a single transmit antennaand a single receive antenna; a single transmit antenna and multiplereceive antennas; and multiple transmit antennas and multiple receiveantennas.
 5. The receiver of claim 1, wherein the soft-bit slicerimplements maximum likelihood soft-bit slicing.
 6. The receiver of claim1, wherein the soft-bit slicer is configurable to accommodate one ormore of the following modulation schemes: BPSK; QPSK; and QAM.
 7. Thereceiver of claim 1, wherein the soft-bit slicer implements thefollowing equation for BPSK modulation:Λ_(R,0)=y_(R), where Λ_(R,0) is a preliminary soft-bit value of aBPSK-modulated transmitted data symbol, and y_(R) is the real part of areceived equalized data stream corresponding to said transmitted datasymbol.
 8. The receiver of claim 1, wherein the soft-bit slicerimplements the following equations for QPSK modulation:Λ_(R,0)=y_(R)Λ_(I,0)=y_(I) where Λ_(R,0) and Λ_(I,0) are respectively preliminarysoft-bit values of the first and second bits in a QPSK-modulatedtransmitted data symbol, and y_(R) and y_(I) are respectively the realand imaginary parts of a received equalized data stream corresponding tosaid transmitted data symbol.
 9. The receiver of claim 1, wherein thesoft-bit slicer implements the following equations for 16-QAMmodulation:Λ_(R,0)=y_(R)Λ_(R,1)=2·(REF*K)−|Λ_(R,0)|Λ_(I,0)=y_(I)Λ_(I,1)=2·(REF*K)−|Λ_(I,0)| where Λ_(R,0), Λ_(R,1), Λ_(I,0), Λ_(I,1) arerespectively preliminary soft-bit values of the first, second, third,and fourth bits in a 16-QAM-modulated transmitted data symbol, y_(R) andy_(I) are respectively the real and imaginary parts of a receivedequalized data stream corresponding to said transmitted data symbol, REFis a mode-dependent constant, and K is a modulation-dependent constant.10. The receiver of claim 1, wherein the soft-bit slicer implements thefollowing equations for 64-QAM modulation:Λ_(R,0)=y_(R)Λ_(R,1)=4·(REF*K)−|Λ_(R,0)|Λ_(R,2)=2·(REF*K)−|Λ_(R,1)|Λ_(I,0)=y_(I)Λ_(I,1)=4·(REF*K)−|Λ_(I,0)|Λ_(I,2)=2·(REF*K)−|Λ_(I,1)| where Λ_(R,0), Λ_(R,1), Λ_(R,2), Λ_(I,0),Λ_(I,1), Λ_(I,2) are respectively preliminary soft-bit values for thefirst, second, third, fourth, fifth, and sixth bits in a64-QAM-modulated transmitted data symbol, y_(R) and y_(I) arerespectively the real and imaginary parts of a received equalized datastream corresponding to said transmitted data symbol, REF is amode-dependent constant, and K a modulation-dependent constant.
 11. Thereceiver of claim 1, wherein the soft-bit slicer implements thefollowing equations for 256-QAM modulation:Λ_(R,0)=y_(R)Λ_(R,1)=8·(REF*K)−|Λ_(R,0)|Λ_(R,2)=4·(REF*K)−|Λ_(R,1)|Λ_(R,3)=2·(REF*K)−|Λ_(R,2)|Λ_(I,0)=y_(I)Λ_(I,1)=8·(REF*K)−|Λ_(I,0)|Λ_(I,2)=4·(REF*K)−|Λ_(I,1)|Λ_(I,3)=2·(REF*K)−|Λ_(I,2)| where Λ_(R,0), Λ_(R,1), Λ_(R,2), Λ_(R,3),Λ_(I,0), Λ_(I,1), Λ_(I,2), Λ_(I,3) are respectively preliminary soft-bitvalues for the first, second, third, fourth, fifth, sixth, seventh, andeighth bits in a 256-QAM-modulated transmitted data symbol, y_(R) andy_(I) are respectively the real and imaginary parts of a receivedequalized data stream corresponding to said transmitted data symbol, REFis a mode-dependent constant, and K a modulation-dependent constant. 12.The receiver of claim 1, wherein the post-scaler multiplies each of saidpreliminary soft-bit values by a scaling factor and amodulation-dependent constant.
 13. The receiver of claim 12, wherein thepost-scaler implements the following equation:L=Λ*SCALE*4*K, where L is a final soft-bit value corresponding to a bitin a received data symbol, Λ is a preliminary soft-bit value receivedfrom the soft-bit slicer, SCALE is a scaling factor, and K is amodulation-dependent constant.
 14. The receiver of claim 13, wherein atleast a portion of the equation implemented by the post-scaler isperformed in a logarithmic domain.
 15. The receiver of claim 2, whereinthe post-scaler uses scaling factors received from the coefficientcalculator to scale the preliminary soft-bit values, such that thegenerated final soft-bit values have uniform dynamic ranges for allmodes of operation and all signal-to-noise ratio (SNR) conditions. 16.The receiver of claim 12, wherein the coefficient calculator generatessaid scaling factors based on noise variance information.